Weihong Han¹, Zhihong Tian^1,*, Zizhong Huang², Lin Zhong³, Yan Jia²

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 167-180, 2019, DOI:10.32604/cmc.2019.05192

Abstract Network Security Situation Awareness System YHSAS acquires, understands and displays the security factors which cause changes of network situation, and predicts the future development trend of these security factors. YHSAS is developed for national backbone network, large network operators, large enterprises and other large-scale network. This paper describes its architecture and key technologies: Network Security Oriented Total Factor Information Collection and High-Dimensional Vector Space Analysis, Knowledge Representation and Management of Super Large-Scale Network Security, Multi-Level, Multi-Granularity and Multi-Dimensional Network Security Index Construction Method, Multi-Mode and Multi-Granularity Network Security Situation Prediction Technology, and so on. The More >

Hongbin Zhang^{1, 2}, Yuzi Yi^{1, *}, Junshe Wang¹, Ning Cao^{3, *}, Qiang Duan⁴

CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 381-399, 2018, DOI:10.3970/cmc.2018.03787

Abstract Network security situation awareness is an important foundation for network security management, which presents the target system security status by analyzing existing or potential cyber threats in the target system. In network offense and defense, the network security state of the target system will be affected by both offensive and defensive strategies. According to this feature, this paper proposes a network security situation awareness method using stochastic game in cloud computing environment, uses the utility of both sides of the game to quantify the network security situation value. This method analyzes the nodes based on… More >

C. Frueh¹

CMES-Computer Modeling in Engineering & Sciences, Vol.111, No.2, pp. 171-201, 2016, DOI:10.3970/cmes.2016.111.171

Abstract In recent years, probabilistic tracking methods have been becoming increasingly popular for solving the multi-target tracking problem in Space Situational Awareness (SSA). Bayesian frameworks have been used to describe the objects' of interest states and cardinality as point processes. The inputs of the Bayesian framework filters are a probabilistic description of the scene at hand, the probability of clutter during the observation, the probability of detection of the objects, the probability of object survival and birth rates, and in the state update, the measurement uncertainty and process noise for the propagation. However, in the filter… More >